Machine learning algorithms analyze environmental and sensor data to predict air pollution levels, helping cities develop strategies to reduce emissions and improve air quality.
In this regards, a monitoring station collected data related to hydrogen sulfide concentration in air asfollows: 23, 25, 26, 26, 29, 30, 30, 31, 32, 32, 35, 35, 35, 35, 40, 43, 43, 45, 45, 45, 45, 46, 50, 55, 56, 62, 80.
a. What is the mean of the data? What is the median? What is the mode?
b. What is sample standard deviation?
c. Compute the five-number summary: min, Q1, median, Q3, max.
d. How outliers can be detected?
e. Develop Box-plot and explain it.